Project plans associated with a resource planning process in a multi-project environment are highly complex and typically hosted in a multi-dimensional database. For example, the plans may include fields such as organizational unit, project name, work package, skill, location, resource pool, employee, month, etc. and values associated with the fields for each record contained in the database. Each field in the database corresponds to a particular level of the project plan data. As such, the low-level source data can be presented at different levels using an appropriate software tool such as a spreadsheet to provide various aggregate views to the user. The low-level source data is manually entered and stored in the database and provides only a bottom-level view of the data. The data can be imported into the spreadsheet for viewing the data at a higher level.
A pivot tool is one such tool for enabling a user to view spreadsheet data in arbitrary aggregate views, i.e. at a higher level. ‘Pivot tool’ in this context refers to a data summarization tool which can sort, count, and total data stored in the spreadsheet and create a so-called pivot table for displaying the summarized data. Pivot tables are useful in presenting high level aggregate views of data such as project planning data or other types of data. However, the lower-level source data imported into the spreadsheet typically must be manually edited if changes are desired based on an analysis of the pivot table content. Manually editing highly detailed low-level data such as complex project planning data can require many hours of manual data manipulation. Also, several iterations of viewing the source data at a higher level using a pivot table and then manually re-editing the low-level data based on the summary provided by the pivot table may be required so that the low-level source data yields the desired high-level aggregate result.
For example, project managers typically manage low-level project planning data by alternating between two different tools in the planning and re-planning process. A data analysis tool is applied, to present a grouped (aggregated) top-down view of the low-level source data loaded from a database. A spreadsheet with a pivot tool add-in is conventionally used to generate an aggregate view of the data. The content of a pivot table can be analyzed with the goal of determining a top-down plan which is consistent with the boundary conditions of the project. A data editing tool such as a web-based editor utility is then applied to the low-level source data, enabling the user to manually enter all bottom-up plan details in a way that the total sums are consistent with the top-down plan view generated using the pivot tool. The editor utility allows data entering on the lowest detail level only. These steps are typically repeated several times to ensure data consistency, increasing cost and delay.